1 00:00:04,400 --> 00:00:07,800 Speaker 1: Welcome to tech Stuff, a production from I Heart Radio. 2 00:00:11,760 --> 00:00:14,160 Speaker 1: Pay there and welcome to tech Stuff. I'm your host, 3 00:00:14,200 --> 00:00:17,000 Speaker 1: Jonathan Strickland. I'm an executive producer with I Heart Radio. 4 00:00:17,040 --> 00:00:19,599 Speaker 1: And how the tech are you? It is time for 5 00:00:19,640 --> 00:00:25,520 Speaker 1: the tech news for Tuesday, July two. And first are 6 00:00:25,640 --> 00:00:30,560 Speaker 1: quick obligatory update on the Elon Musk Twitter situation. Twitter 7 00:00:30,600 --> 00:00:34,000 Speaker 1: wants to take Musk to court as early as September 8 00:00:34,800 --> 00:00:37,560 Speaker 1: uh in order to force him to acquire the company 9 00:00:37,600 --> 00:00:40,840 Speaker 1: that he agreed to acquire. Musk has argued that more 10 00:00:40,920 --> 00:00:44,280 Speaker 1: time is needed to prove that Twitter is infested with 11 00:00:44,360 --> 00:00:47,440 Speaker 1: bots to a point that would justify backing out of 12 00:00:47,479 --> 00:00:50,800 Speaker 1: the agreement to purchase the company, so he wants to 13 00:00:50,840 --> 00:00:54,280 Speaker 1: push the trial to February of next year. Late February, 14 00:00:54,600 --> 00:00:57,959 Speaker 1: i might add, and today a judge will hear Twitter's 15 00:00:58,080 --> 00:01:01,400 Speaker 1: motion for a September trial make a decision on that. 16 00:01:01,560 --> 00:01:04,479 Speaker 1: So it's possible that later this week we'll actually know 17 00:01:04,720 --> 00:01:07,560 Speaker 1: when this is going to head to the courts. The 18 00:01:07,640 --> 00:01:11,480 Speaker 1: general sense that I'm picking up reading various analysts takes 19 00:01:11,520 --> 00:01:16,760 Speaker 1: about this case is that Musk's argument is exceedingly weak. 20 00:01:16,800 --> 00:01:19,160 Speaker 1: A lot of folks feel that it's pretty much all 21 00:01:19,200 --> 00:01:22,360 Speaker 1: but guaranteed that the courts will force him to either 22 00:01:22,480 --> 00:01:25,119 Speaker 1: go through the deal or he'll have to pay a 23 00:01:25,200 --> 00:01:28,640 Speaker 1: hefty settlement to get out of it. But don't take 24 00:01:28,920 --> 00:01:32,400 Speaker 1: anything for granted. When it comes to Elon Musk. Sometimes 25 00:01:32,480 --> 00:01:36,280 Speaker 1: the absurd is normal. So while that seems to be 26 00:01:36,360 --> 00:01:40,520 Speaker 1: the general sense at the moment, doesn't necessarily mean that's 27 00:01:40,520 --> 00:01:44,080 Speaker 1: where things are going to head. Albania's government has been 28 00:01:44,080 --> 00:01:49,520 Speaker 1: digitizing its agencies over the recent past, and it launched 29 00:01:49,560 --> 00:01:53,600 Speaker 1: an online portal for most government agencies and departments earlier 30 00:01:53,640 --> 00:01:56,360 Speaker 1: this year. Now, the government has had to take those 31 00:01:56,360 --> 00:02:00,000 Speaker 1: websites offline because of a cyber attack. The government said 32 00:02:00,040 --> 00:02:04,720 Speaker 1: the attack was synchronized and sophisticated, and that it originated 33 00:02:04,800 --> 00:02:08,760 Speaker 1: outside of Albania. The government is currently working with Microsoft 34 00:02:08,760 --> 00:02:11,560 Speaker 1: as well as a cybersecurity company to get systems back 35 00:02:11,560 --> 00:02:15,400 Speaker 1: online and safe from further attacks. No word as of 36 00:02:15,440 --> 00:02:17,960 Speaker 1: the time of this recording on who was responsible for 37 00:02:18,040 --> 00:02:22,040 Speaker 1: carrying out those attacks or what their goal was beyond disruption. 38 00:02:22,760 --> 00:02:25,600 Speaker 1: Russia has hit Google with a twenty one point one 39 00:02:25,919 --> 00:02:30,720 Speaker 1: billion rouble fine that amounts to about three seventy four 40 00:02:30,760 --> 00:02:34,320 Speaker 1: million dollars, and you might wonder Okay, well, what's the deal. Well, 41 00:02:34,320 --> 00:02:37,200 Speaker 1: the Russian government says that Google has failed to remove 42 00:02:37,280 --> 00:02:44,200 Speaker 1: prohibited information, namely information regarding Russia's invasion and war in Ukraine. 43 00:02:45,000 --> 00:02:49,440 Speaker 1: Google has also blocked state backed Russian media from posting 44 00:02:49,520 --> 00:02:52,799 Speaker 1: on platforms like YouTube. So that is a double whammy 45 00:02:52,919 --> 00:02:55,919 Speaker 1: against the Russian government, which has been leaning really hard 46 00:02:55,960 --> 00:02:59,200 Speaker 1: on its propaganda machine to fight back against Russian citizens 47 00:02:59,240 --> 00:03:03,320 Speaker 1: opposition to the war in Ukraine. The Affinity Credit Union, 48 00:03:03,480 --> 00:03:07,080 Speaker 1: which is based in the United States state of Iowa, 49 00:03:07,200 --> 00:03:11,760 Speaker 1: has filed a lawsuit against Apple. At the heart of 50 00:03:11,760 --> 00:03:14,920 Speaker 1: this complaint is yet another charge of Apple engaging in 51 00:03:15,000 --> 00:03:18,240 Speaker 1: anti competitive practices, something we've heard a lot of in 52 00:03:18,280 --> 00:03:22,280 Speaker 1: the recent past. This time it's regarding its mobile wallet 53 00:03:22,400 --> 00:03:27,280 Speaker 1: and contactless payment system. So essentially, this lawsuit argues that 54 00:03:27,320 --> 00:03:31,040 Speaker 1: Apple requires all payment card issuers that is, credit cards 55 00:03:31,040 --> 00:03:35,520 Speaker 1: and debit cards to use Apple's mobile wallet if they 56 00:03:35,560 --> 00:03:38,600 Speaker 1: want their customers to be able to use contactless payment. 57 00:03:39,120 --> 00:03:43,360 Speaker 1: Apple only allows its own digital wallet to use that feature, 58 00:03:43,840 --> 00:03:47,560 Speaker 1: so while you could download a different digital wallet on 59 00:03:47,640 --> 00:03:50,360 Speaker 1: an iOS device, that wallet would not be able to 60 00:03:50,400 --> 00:03:55,240 Speaker 1: take advantage of contactless payment. Further, to get access to 61 00:03:55,400 --> 00:03:58,640 Speaker 1: Apple's mobile wallet, payment card issuers have to pay a 62 00:03:58,760 --> 00:04:02,640 Speaker 1: fee on all credit or debit transactions. Now, if you 63 00:04:02,760 --> 00:04:06,520 Speaker 1: contrast that with Android, you can actually on an Android 64 00:04:06,560 --> 00:04:10,280 Speaker 1: device have all sorts of different mobile wallets downloaded to 65 00:04:10,400 --> 00:04:13,360 Speaker 1: the device, and all of them can use contactless payment, 66 00:04:13,720 --> 00:04:17,160 Speaker 1: and they don't levy fees on payment card issuers. And 67 00:04:17,200 --> 00:04:19,000 Speaker 1: so you can see where there's some fuel for a 68 00:04:19,080 --> 00:04:22,520 Speaker 1: lawsuit here. Apple has been the target of numerous lawsuits 69 00:04:22,520 --> 00:04:26,400 Speaker 1: like this one fairly recently, as more companies and governments 70 00:04:26,400 --> 00:04:29,599 Speaker 1: scrutinized the company's practices, and over the last few years, 71 00:04:30,000 --> 00:04:32,720 Speaker 1: Apple has really leaned more heavily on being a company 72 00:04:32,760 --> 00:04:37,200 Speaker 1: that offers and facilitates services more than being a company 73 00:04:37,279 --> 00:04:42,839 Speaker 1: known for focusing on new innovative hardware. Of course, Apple 74 00:04:42,920 --> 00:04:46,479 Speaker 1: still does make hardware, still releases hardware. We still get 75 00:04:46,520 --> 00:04:49,680 Speaker 1: new iPhones and and Max and all that kind of stuff, 76 00:04:50,839 --> 00:04:54,200 Speaker 1: But it's been a few years since Apple has really 77 00:04:54,240 --> 00:04:59,719 Speaker 1: been touted as an innovative hardware company, and Tim Cook 78 00:05:00,320 --> 00:05:04,520 Speaker 1: has really put a lot of enthusiasm behind developing Apple 79 00:05:04,560 --> 00:05:08,240 Speaker 1: as a services company, because, of course, you can only 80 00:05:08,279 --> 00:05:11,360 Speaker 1: sell a piece of hardware to a person once, right, 81 00:05:11,760 --> 00:05:14,800 Speaker 1: If I sell you an iPhone. I can't sell that 82 00:05:14,839 --> 00:05:17,840 Speaker 1: same iPhone a second time. But if I get you 83 00:05:18,040 --> 00:05:21,960 Speaker 1: on a service that has a recurring subscription fee, I 84 00:05:22,000 --> 00:05:26,760 Speaker 1: can have a paying customer for you know, an indeterminate 85 00:05:26,760 --> 00:05:29,200 Speaker 1: amount of time. It's not just a one time thing. 86 00:05:29,800 --> 00:05:32,960 Speaker 1: So Tim Cook has really pushed the company into that 87 00:05:33,200 --> 00:05:37,000 Speaker 1: kind of revenue model. However, the structures that Apple has 88 00:05:37,000 --> 00:05:39,200 Speaker 1: built in order to give itself a dominant position on 89 00:05:39,240 --> 00:05:42,359 Speaker 1: its own platform has brought it under scrutiny, and it 90 00:05:42,440 --> 00:05:44,760 Speaker 1: may turn out that this focus on services is going 91 00:05:44,839 --> 00:05:47,039 Speaker 1: to cause a lot more headaches as Apple tries to 92 00:05:47,080 --> 00:05:51,880 Speaker 1: avoid accusations of restricting competition on its own platforms. Well, 93 00:05:52,040 --> 00:05:55,039 Speaker 1: I don't know if you happen to know this, but 94 00:05:55,200 --> 00:05:58,479 Speaker 1: we are still in the middle of a pandemic. Anyway. 95 00:05:58,520 --> 00:06:02,440 Speaker 1: That pandemic has forced some rapid and dramatic changes across 96 00:06:02,480 --> 00:06:05,680 Speaker 1: our lives, which is again staying the obvious and then 97 00:06:05,720 --> 00:06:08,320 Speaker 1: includes how we work. And that leads us to our 98 00:06:08,360 --> 00:06:11,279 Speaker 1: next story, which is that Meta, the company that owns 99 00:06:11,360 --> 00:06:14,919 Speaker 1: you know, Facebook and Instagram, has discovered that when hiring 100 00:06:14,960 --> 00:06:18,680 Speaker 1: folks who wanted to work remotely, they actually saw an 101 00:06:18,760 --> 00:06:23,520 Speaker 1: unexpected side benefit that the new hires were more diverse 102 00:06:24,120 --> 00:06:26,520 Speaker 1: than what the company typically saw when it would hire 103 00:06:26,560 --> 00:06:29,760 Speaker 1: new employees who were coming into work at the office. 104 00:06:30,360 --> 00:06:32,880 Speaker 1: So there were more women and there were more people 105 00:06:32,960 --> 00:06:36,120 Speaker 1: of color in the hires that they were bringing on. 106 00:06:36,520 --> 00:06:39,320 Speaker 1: The Washington Post ran an article about this, showing that 107 00:06:39,400 --> 00:06:43,320 Speaker 1: the hiring saw people from underrepresentative groups joining the company 108 00:06:43,360 --> 00:06:47,680 Speaker 1: in larger numbers than before. Now, I've always been a 109 00:06:47,720 --> 00:06:51,760 Speaker 1: big proponent of purposefully making moves like that, you know, 110 00:06:51,800 --> 00:06:56,000 Speaker 1: actively and consciously working to diversify our workforce because more 111 00:06:56,080 --> 00:07:00,159 Speaker 1: perspectives and different ways of coming up with ideas have 112 00:07:00,200 --> 00:07:03,280 Speaker 1: an enormous benefit on the company's operations, and it can 113 00:07:03,320 --> 00:07:06,080 Speaker 1: also help a company avoid making decisions that would in 114 00:07:06,279 --> 00:07:09,200 Speaker 1: hindsight be viewed as being what I like to call 115 00:07:09,920 --> 00:07:14,040 Speaker 1: bone headed, or misogynistic or racist. It's good to have 116 00:07:14,160 --> 00:07:17,720 Speaker 1: voices that can say, hey, that's not such a good 117 00:07:17,760 --> 00:07:23,000 Speaker 1: idea on occasion. Anyway. This report suggests that these underrepresented 118 00:07:23,000 --> 00:07:27,680 Speaker 1: groups are more comfortable working remotely, and it further indicates 119 00:07:27,720 --> 00:07:31,560 Speaker 1: that Silicon Valley offices aren't really known for their diversity, 120 00:07:32,080 --> 00:07:36,560 Speaker 1: so not surprisingly, the region isn't really favored by underrepresented 121 00:07:36,600 --> 00:07:43,800 Speaker 1: groups who might feel pressured or they might encounter microaggressions 122 00:07:44,320 --> 00:07:47,520 Speaker 1: as they go to the office every day, and of 123 00:07:47,560 --> 00:07:51,000 Speaker 1: course by working from home, they sidestep a lot of 124 00:07:51,040 --> 00:07:55,080 Speaker 1: that and it ends up causing less stress on their 125 00:07:55,120 --> 00:07:58,040 Speaker 1: lives as they try and do their jobs. So when 126 00:07:58,080 --> 00:08:00,280 Speaker 1: I read these articles, I realized that, you know, listening 127 00:08:00,480 --> 00:08:03,440 Speaker 1: really is important and that folks like me need to 128 00:08:03,440 --> 00:08:07,800 Speaker 1: do a lot more listening. Anyway, it was interesting consequence 129 00:08:07,880 --> 00:08:10,120 Speaker 1: that that followed the move to remote work, you know, 130 00:08:10,200 --> 00:08:14,160 Speaker 1: to see this increase in diversity, and hopefully we'll see 131 00:08:14,200 --> 00:08:17,600 Speaker 1: increase diversity in Meta and other tech companies moving forward, 132 00:08:17,640 --> 00:08:22,440 Speaker 1: because honestly, we all benefit from that. One issue that 133 00:08:22,520 --> 00:08:26,880 Speaker 1: has plagued Amazon, apart from its workers having the temerity 134 00:08:26,960 --> 00:08:31,120 Speaker 1: to want to unionize the radicals, is the issue of 135 00:08:31,320 --> 00:08:35,440 Speaker 1: fake reviews. UH. Fake reviews skew results in Amazon's searches, 136 00:08:35,880 --> 00:08:38,960 Speaker 1: and they guide people to purchasing products that don't justify 137 00:08:39,040 --> 00:08:41,400 Speaker 1: the glowing five star ratings that have been posted by 138 00:08:41,440 --> 00:08:45,679 Speaker 1: fake accounts or people who are paid or otherwise compensated 139 00:08:45,720 --> 00:08:49,959 Speaker 1: in order to generate positive reviews. And Amazon has made 140 00:08:49,960 --> 00:08:52,439 Speaker 1: another big move to push back against this trend of 141 00:08:52,480 --> 00:08:55,559 Speaker 1: fake reviews by taking legal action against more than ten 142 00:08:55,920 --> 00:09:01,000 Speaker 1: thousand Facebook group administrators. So those groups, according to Amazon, 143 00:09:01,440 --> 00:09:05,880 Speaker 1: coordinate and facilitate fake reviews for Amazon products or products 144 00:09:05,880 --> 00:09:09,320 Speaker 1: that are listed on Amazon, not just Amazon products, and 145 00:09:09,559 --> 00:09:12,400 Speaker 1: they promised free stuff to folks who will post fake 146 00:09:12,440 --> 00:09:15,880 Speaker 1: reviews for a selection of products. Amazon has been waging 147 00:09:15,920 --> 00:09:18,040 Speaker 1: war against fake reviews for a while now, going so 148 00:09:18,080 --> 00:09:20,640 Speaker 1: far as to ban certain merchants from the platform, even 149 00:09:20,760 --> 00:09:24,120 Speaker 1: really big notable ones. But this is interesting to see 150 00:09:24,120 --> 00:09:27,400 Speaker 1: them going after the groups that are meant to to 151 00:09:27,640 --> 00:09:32,480 Speaker 1: recruit people to post these fake reviews. Okay, we're gonna 152 00:09:32,520 --> 00:09:34,320 Speaker 1: take a quick break and when we come back, we'll 153 00:09:34,360 --> 00:09:45,480 Speaker 1: have a few more news items. Okay, we're back. Next 154 00:09:45,520 --> 00:09:49,120 Speaker 1: news item up. Clear Trip a flight booking website that's 155 00:09:49,160 --> 00:09:53,080 Speaker 1: popular in India. Though lots of places actually use clear Trip, 156 00:09:53,120 --> 00:09:56,960 Speaker 1: it's just mostly used in India. Uh. It's also accompanied 157 00:09:57,000 --> 00:09:59,680 Speaker 1: by the way that Walmart has a majority ownership in 158 00:10:00,400 --> 00:10:03,600 Speaker 1: has recently had a data breach that was serious enough 159 00:10:03,640 --> 00:10:06,800 Speaker 1: to prompt the company to alert customers about it. The 160 00:10:06,840 --> 00:10:10,760 Speaker 1: company says that someone gained illegal and unauthorized access to 161 00:10:11,000 --> 00:10:15,000 Speaker 1: quote a part of clear trips internal systems end quote. 162 00:10:15,520 --> 00:10:19,080 Speaker 1: They also said the intrusion only essentially scraped surface level 163 00:10:19,200 --> 00:10:23,000 Speaker 1: data like a customer's profile information, but not like their 164 00:10:23,040 --> 00:10:27,160 Speaker 1: sensitive info like passwords and payment methods and such, although 165 00:10:27,160 --> 00:10:28,680 Speaker 1: they did say, hey, if it makes you feel better, 166 00:10:28,679 --> 00:10:32,640 Speaker 1: you can reset your password. The newspaper The Register contacted 167 00:10:32,640 --> 00:10:35,280 Speaker 1: clear Trip to get more information about this. They asked 168 00:10:35,320 --> 00:10:39,680 Speaker 1: what data did the intruders specifically gain access to, how 169 00:10:39,760 --> 00:10:42,920 Speaker 1: much were they able to access, how did they gain 170 00:10:42,960 --> 00:10:46,520 Speaker 1: access into the system in the first place, did they 171 00:10:46,559 --> 00:10:50,440 Speaker 1: extract any information? Is that detectable? And when the heck 172 00:10:50,480 --> 00:10:53,800 Speaker 1: did this happen? And when did clear Trip actually alert customers? 173 00:10:54,240 --> 00:10:56,840 Speaker 1: Now when it happened is a big deal because India 174 00:10:56,880 --> 00:10:59,240 Speaker 1: has a law that states any company that detects a 175 00:10:59,320 --> 00:11:02,680 Speaker 1: data breach has the responsibility to report the breach to 176 00:11:02,720 --> 00:11:06,800 Speaker 1: authorities within six hours. Anyway, as of this recording, clear 177 00:11:06,840 --> 00:11:10,679 Speaker 1: Trip had not clarified the matter. Samsung tweeted out a 178 00:11:10,760 --> 00:11:14,160 Speaker 1: series of messages that created a puzzle for the curious. 179 00:11:14,480 --> 00:11:18,600 Speaker 1: The puzzle included a message saying when will something greater arrive? 180 00:11:19,400 --> 00:11:22,680 Speaker 1: And then this was followed by six circles, and each 181 00:11:22,679 --> 00:11:26,960 Speaker 1: circle had had slightly different shades different colors of circles, 182 00:11:27,000 --> 00:11:30,520 Speaker 1: and another message had a grid of letters symbols and 183 00:11:30,640 --> 00:11:35,240 Speaker 1: numbers arranged. And then a third message had a a 184 00:11:35,360 --> 00:11:38,920 Speaker 1: grid similar grid, same with same height, but instead of 185 00:11:39,040 --> 00:11:43,280 Speaker 1: numbers and symbols and such, it had circles with different 186 00:11:43,280 --> 00:11:47,920 Speaker 1: colors in them. Now collectively that puzzle would reveal a date. 187 00:11:47,960 --> 00:11:49,560 Speaker 1: And see what would happen is you would have to 188 00:11:49,600 --> 00:11:53,079 Speaker 1: look at those six circles in the first picture, and 189 00:11:53,120 --> 00:11:57,240 Speaker 1: then you would find identical shaded circles that were in 190 00:11:57,280 --> 00:11:59,400 Speaker 1: the third picture of the circles that were in the grid. 191 00:11:59,640 --> 00:12:02,240 Speaker 1: So you'd find the ones that matched the shade, so 192 00:12:02,360 --> 00:12:06,800 Speaker 1: circle number one had matched a specific circle within the grid. 193 00:12:07,640 --> 00:12:13,040 Speaker 1: Then you would look for the corresponding symbol that was 194 00:12:13,080 --> 00:12:15,760 Speaker 1: in the same same position of the grid on picture 195 00:12:15,840 --> 00:12:18,280 Speaker 1: number two. I know it sounds confusing, but ultimately, if 196 00:12:18,280 --> 00:12:21,480 Speaker 1: you did all this matching, you would discover that the 197 00:12:21,600 --> 00:12:26,160 Speaker 1: an original message was spelling out the date zero eight 198 00:12:26,679 --> 00:12:30,440 Speaker 1: one zero to two, which if we're reading dates the 199 00:12:30,440 --> 00:12:33,840 Speaker 1: way we Americans do, which is the right way, that 200 00:12:33,840 --> 00:12:37,840 Speaker 1: would be August two. Of course, could be that we're 201 00:12:37,840 --> 00:12:40,160 Speaker 1: supposed to read the date the wrong way, in which 202 00:12:40,240 --> 00:12:44,360 Speaker 1: case it's the eighth of October. But you know that 203 00:12:44,360 --> 00:12:46,400 Speaker 1: would just be silly, right it's gotta be August right 204 00:12:47,160 --> 00:12:50,080 Speaker 1: either way, most folks expect Samsung will be announcing a 205 00:12:50,120 --> 00:12:53,320 Speaker 1: few new products, including a Galaxy Fold four, a Galaxy 206 00:12:53,360 --> 00:12:57,280 Speaker 1: Flip four, and a Galaxy Watch five. Hopefully the announcement 207 00:12:57,320 --> 00:13:00,640 Speaker 1: itself will be more exciting than the puzzle was. Earlier 208 00:13:00,679 --> 00:13:03,240 Speaker 1: in this episode, I talked about how Elon Musk is 209 00:13:03,320 --> 00:13:06,559 Speaker 1: leaning hard on the bots issue on Twitter to justify 210 00:13:06,640 --> 00:13:10,080 Speaker 1: backing out of the acquisition deal. Well, other folks apparently 211 00:13:10,160 --> 00:13:13,320 Speaker 1: leaned on bots hard to elevate the call for Warner 212 00:13:13,360 --> 00:13:16,640 Speaker 1: Brothers to release the so called Snyder cut of the 213 00:13:16,760 --> 00:13:20,640 Speaker 1: Justice League movie. Rolling Stone reports that fake accounts and 214 00:13:20,679 --> 00:13:23,280 Speaker 1: bots amplified the message and that it was above the 215 00:13:23,320 --> 00:13:26,480 Speaker 1: normal threshold. You know, bots usually make up three to 216 00:13:26,600 --> 00:13:29,800 Speaker 1: five percent of all accounts that are involved in conversations 217 00:13:29,840 --> 00:13:33,079 Speaker 1: on trending topics, but when it came to the Snyder cut, 218 00:13:33,440 --> 00:13:37,760 Speaker 1: it was more like thirteen. Now, granted, that still means 219 00:13:37,800 --> 00:13:41,000 Speaker 1: around seven of all the accounts that we're calling for 220 00:13:41,040 --> 00:13:45,000 Speaker 1: a Snyder cut were legitimate. They were from real users, 221 00:13:45,040 --> 00:13:48,760 Speaker 1: So it's not like this was a holy manufactured online crusade, 222 00:13:49,200 --> 00:13:53,679 Speaker 1: but it is an interesting outlier. Like why why this 223 00:13:53,760 --> 00:13:57,040 Speaker 1: topic why were more bots calling for this than anything else. 224 00:13:57,840 --> 00:14:01,240 Speaker 1: Warner Media actually investigated the issue after receiving numerous complaints 225 00:14:01,280 --> 00:14:03,160 Speaker 1: that the call for the Snyder cut wasn't all it 226 00:14:03,240 --> 00:14:07,760 Speaker 1: appeared to be, which makes you wonder why, Like, why 227 00:14:07,840 --> 00:14:10,320 Speaker 1: was this such a big deal? Why were people so 228 00:14:10,440 --> 00:14:12,440 Speaker 1: upset one way or the other? I mean, I get why, 229 00:14:12,600 --> 00:14:17,120 Speaker 1: like fans wanted to see what the original intended movie was, 230 00:14:17,840 --> 00:14:20,479 Speaker 1: but I don't. I don't know why there was controversy 231 00:14:20,560 --> 00:14:24,240 Speaker 1: on either side apart from like some other issues with Snyder, 232 00:14:24,400 --> 00:14:28,160 Speaker 1: But I don't know. This one really confuses me. And 233 00:14:28,200 --> 00:14:31,480 Speaker 1: why bring bots into it? Then? I need to know, 234 00:14:31,920 --> 00:14:34,720 Speaker 1: So I'm hoping that we learned more about this. The 235 00:14:34,880 --> 00:14:37,720 Speaker 1: M I T Technology Review has a fun article titled 236 00:14:37,920 --> 00:14:41,960 Speaker 1: Sony's Racing AI destroyed its human competitors by being nice 237 00:14:42,560 --> 00:14:46,680 Speaker 1: and fast. So we're talking about car racing here, and 238 00:14:46,720 --> 00:14:50,200 Speaker 1: we're actually talking about video game or simulated car racing. 239 00:14:50,280 --> 00:14:53,800 Speaker 1: Using Grand Tarismo as the game engine, so to speak, 240 00:14:54,520 --> 00:14:57,520 Speaker 1: Sony developed an AI that could operate within the rules 241 00:14:57,640 --> 00:15:00,840 Speaker 1: of the game. So by that, I mean this AI 242 00:15:01,120 --> 00:15:04,400 Speaker 1: was operating like an actual driver. It was not able 243 00:15:04,440 --> 00:15:07,320 Speaker 1: to bend physics and cheat. I know, Anyone who's played 244 00:15:07,560 --> 00:15:11,960 Speaker 1: racing games knows that sometimes these games will fudge the 245 00:15:12,000 --> 00:15:14,720 Speaker 1: physics a bit, like there's always cases with things like 246 00:15:14,800 --> 00:15:19,560 Speaker 1: rubber banding. Rubber Banding is when um the the You know, 247 00:15:19,640 --> 00:15:21,600 Speaker 1: if if you get too far ahead of all the 248 00:15:21,680 --> 00:15:25,000 Speaker 1: AI controlled cars, they suddenly magically catch up to you, 249 00:15:25,080 --> 00:15:27,400 Speaker 1: as if they were attached to you by an invisible 250 00:15:27,480 --> 00:15:30,120 Speaker 1: rubber band. That was not going on here, at least 251 00:15:30,120 --> 00:15:32,240 Speaker 1: according to Sony that was not the case. Like this 252 00:15:32,360 --> 00:15:35,480 Speaker 1: was all legit where the AI had to operate by 253 00:15:35,520 --> 00:15:39,240 Speaker 1: the same rules as any human driver would, and it 254 00:15:39,440 --> 00:15:43,920 Speaker 1: quickly showed that on a blank racetrack it could. It 255 00:15:43,920 --> 00:15:47,560 Speaker 1: could actually race faster than humans could. It didn't do 256 00:15:47,720 --> 00:15:51,760 Speaker 1: so well in full races, like when the racetrack had 257 00:15:51,960 --> 00:15:55,400 Speaker 1: a whole group of human drivers in it. The AI 258 00:15:55,560 --> 00:15:59,040 Speaker 1: wasn't as competitive until Sony went and tweaked the AI 259 00:15:59,480 --> 00:16:01,840 Speaker 1: brought it back, and then it did really well and 260 00:16:01,920 --> 00:16:05,520 Speaker 1: was able to beat human drivers again. The AI, which 261 00:16:05,960 --> 00:16:10,000 Speaker 1: is called Gt. Sophie, interacts with the game ten times 262 00:16:10,000 --> 00:16:13,760 Speaker 1: a second. It collects information about the AI vehicle's position 263 00:16:13,840 --> 00:16:16,400 Speaker 1: relative to the track as well as relative to the 264 00:16:16,400 --> 00:16:19,560 Speaker 1: other racers, and it also tracks the physical forces that 265 00:16:19,560 --> 00:16:21,960 Speaker 1: are all acting upon the vehicle, which means that quote 266 00:16:22,040 --> 00:16:24,920 Speaker 1: unquote knows when to do things like apply the brakes 267 00:16:25,160 --> 00:16:28,479 Speaker 1: or begin a turn without pushing the car past its limitations. 268 00:16:29,120 --> 00:16:31,280 Speaker 1: The article goes into a bit more detail as to 269 00:16:31,360 --> 00:16:34,240 Speaker 1: the process that Sony used to train the AI, and 270 00:16:34,280 --> 00:16:37,360 Speaker 1: it's really interesting stuff. So if you're interested in this topic, 271 00:16:37,400 --> 00:16:39,800 Speaker 1: I recommend you check that article out again. It is 272 00:16:39,840 --> 00:16:43,640 Speaker 1: titled Sony's Racing AI destroyed its human competitors by being 273 00:16:43,720 --> 00:16:46,840 Speaker 1: nice and fast, and it's in the M I T 274 00:16:46,840 --> 00:16:52,400 Speaker 1: Technology Review. Finally, and in similar news, Microsoft recently announced 275 00:16:52,440 --> 00:16:56,760 Speaker 1: Project air Sim, which quote uses the power of Azure 276 00:16:56,920 --> 00:17:00,640 Speaker 1: to generate massive amounts of data for training AIM models 277 00:17:00,680 --> 00:17:03,560 Speaker 1: on exactly which actions to take at each phase of 278 00:17:03,640 --> 00:17:08,360 Speaker 1: flight from takeoff to cruising to landing end quote. According 279 00:17:08,400 --> 00:17:12,240 Speaker 1: to Jake's Siegel of Microsoft, the idea is that Project 280 00:17:12,280 --> 00:17:15,720 Speaker 1: air Sim will create realistic simulations of various flight conditions 281 00:17:15,720 --> 00:17:18,560 Speaker 1: while training AI on how to pilot an aircraft in 282 00:17:18,600 --> 00:17:22,879 Speaker 1: those situations, all with the goal to accelerate autonomous aircraft development. 283 00:17:23,520 --> 00:17:26,080 Speaker 1: And when I say aircraft, you could really substitute the 284 00:17:26,080 --> 00:17:29,960 Speaker 1: word drone in there pretty reliably. So Microsoft has built 285 00:17:29,960 --> 00:17:33,440 Speaker 1: a platform that will allow drone manufacturers to refine their 286 00:17:33,480 --> 00:17:37,840 Speaker 1: autonomous flying systems. This product replaces an earlier one that 287 00:17:37,920 --> 00:17:40,879 Speaker 1: was just called air sim, but that one required customers 288 00:17:40,880 --> 00:17:44,360 Speaker 1: to have a deeper knowledge and experience with machine learning systems. 289 00:17:44,880 --> 00:17:48,199 Speaker 1: Project air sim simplifies matters. It kind of keeps all 290 00:17:48,200 --> 00:17:51,360 Speaker 1: that pesky coding stuff behind a user interface that's more 291 00:17:51,400 --> 00:17:54,840 Speaker 1: intuitive for customers to use. And that's it for the 292 00:17:54,840 --> 00:17:59,240 Speaker 1: news for Tuesday, July two thousand twenty two. If you 293 00:17:59,320 --> 00:18:02,720 Speaker 1: have any suggestions for future topics on tech Stuff, please 294 00:18:02,760 --> 00:18:04,320 Speaker 1: reach out to me. 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